Adaptive Image Enhancement Algorithm with Complex Background

ABSTRACT

How to capture and enhance the target from an image with complex texture and edge features is studied in this paper. For the traditional image enhancement methods can not split different kinds of the textures and edges of an image efficiently, a novel adaptive enhancement algorithm based on nonsubsampled contourlet transform (NSCT) is projected. Firstly, by using the direct spatial multiplication of NSCT coefficients of each same directional subband at adjacent highpass scales, the inter-scale spaces are constructed and the optimal geometrical directions of each matrix region are calculated in the proposed spaces. Experimental results show that, in NSCT domain, the geometrical direction information which locates in the inter-scale spaces can represent the different detail features exactly of an image. Therefore, the optimal geometrical direction information as a rule to determine what kind of edge and texture features would be captured and enhanced is employed. After comparing with existing enhancement method, the proposed approach achieves better results, not only clearly identifies target edges and textures from complex background, but also enhances them with better visualization.

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